作业帮谁能帮我在IEEE上下载一篇文献啊?
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谁能帮我在IEEE上下载一篇文献啊?
A simple and efficient estimator for hyperbolic location
IEEE Trans on Signal Processing 1994 Page(s): 1905 - 1915
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A simple and efficient estimator for hyperbolic location
IEEE Trans on Signal Processing 1994 Page(s): 1905 - 1915
邮箱：haha_4321@126.com
很急啊 多谢帮忙了!
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A Simple and Efficient Estimator for Hyperbolic Location
Y. T. Chm, Senior Member, IEEE, and K. C. Ho, Member, IEEE
Abstract
An effective technique in locating a source based on intersections of hyperbolic curves defined by the time differences of arrival of a signal received at a number of sensors is proposed. The approach is noniterative and gives an explicit solution. It is an approximate realization of the maximum-likelihood estimator and is shown to attain the Cramer-Rao lower bound near the small error region. Comparisons of performance with existing techniques of beamformer, spherical-interpolation, divide and conquer, and iterative Taylor-series methods are made. The proposed technique performs significantly better than spherical-interpolation, and has a higher noise threshold than divide and conquer before performance breaks away from the Cramer-Rao lower bound. It provides an explicit solution form that is not available in the beamforming and Taylor-series methods. Computational complexity is comparable to spherical-interpolation but substantially less than the Taylor-series method
A Simple and Efficient Estimator for Hyperbolic Location
Y. T. Chm, Senior Member, IEEE, and K. C. Ho, Member, IEEE
Abstract
An effective technique in locating a source based on intersections of hyperbolic curves defined by the time differences of arrival of a signal received at a number of sensors is proposed. The approach is noniterative and gives an explicit solution. It is an approximate realization of the maximum-likelihood estimator and is shown to attain the Cramer-Rao lower bound near the small error region. Comparisons of performance with existing techniques of beamformer, spherical-interpolation, divide and conquer, and iterative Taylor-series methods are made. The proposed technique performs significantly better than spherical-interpolation, and has a higher noise threshold than divide and conquer before performance breaks away from the Cramer-Rao lower bound. It provides an explicit solution form that is not available in the beamforming and Taylor-series methods. Computational complexity is comparable to spherical-interpolation but substantially less than the Taylor-series method
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